The inevitable approach of CMOS scaling law to saturation drives the current impetus of the scientific community to search for novel material, device, circuit, and system concepts to foster progress in the post-Moore electronics era. In particular, the goal is to develop those solutions which allow us to sense, process, and store data similarly as natural systems do. In this respect memristor technologies represent a key to open a new bio-inspired approach to the design of future electrical circuits. With their extraordinary capability to merge data detection, storage and processing in the same physical medium, memristors enable the hardware realizations of revolutionary computing paradigms inspired to the operating principles of biological systems. In particular, this makes it possible to eliminate the von Neumann bottleneck which impairs time, energy, heat, and area measures of performance of state-of-the-art computing machines. Novel groundbreaking architectures, including in-memory computing crossbars, memcomputing Cellular Neural Networks, as well as locally active memristive data processors, inspired to the structure, morphology, and functionality of the human brain, are the subject of intensive and extensive research in industry and academia worldwide. These new architectures shall enable a new way of processing information, allowing an intelligent and efficient management of auditory, tactile, vision, and even olfactory sensory data, fulfilling the challenging requirements of the Internet-of-Things and Edge Computing industries. The proposed special session intends to present the latest theoretico-experimental advances in memristor technology, including topics spanning from material engineering to computer architecture via device fabrication, characterization, and modelling, as well as circuit and system analysis and design. This scientific forum shall bring together scientists with different yet complementary academic backgrounds to encourage knowledge sharing, idea exchanges, and cooperations in the multidisciplinary research field of memristors. The session will further provide early-career scientists with the opportunity to learn about the latest developments and research trends, open questions, and future directions in this exciting research field. The special session shall cover, but is not limited to, the topics to follow:

·        Emerging Memristor Device Technologies

·        Material Engineering Practices

·        Nanotechnology Applications

·        In-Memory Sensing-and-Computing Paradigms

·        Computational Perception and Cognition Concepts

·        Circuit and System Theory

·        Bio-Inspired Analog Circuit Design

·        Cellular Neural Networks

·        Spiking Neural Networks

·        Neuromorphic Engineering

·        Software Engineering

Special Session Organizers:

Alon Ascoli (Senior IEEE Member) received the Ph.D. Degree in Electronic Engineering from University College Dublin in 2006. Since Dec. 2023 he is with the Department of Electronics and Telecommunications, Politecnico di Torino, Turin, Italy. From Dec. 2012 to Nov. 2023, he was affiliated with the Faculty of Electrical and Computer Engineering, TUD | Dresden University of Technology. He develops circuit- and system-theoretic methods for the analysis and design of bio-inspired memristive circuits, enabling to deepen our understanding of biological systems and/or to extend the functionalities of traditional electronic systems. He was conferred the Habilitation title as Full (Associate) Professor in Electrical Circuit Theory from the Italian Ministry of Education in 2023 (2017), and the Habilitation title as Full Professor in Nonlinear Circuit Theory from TU Dresden in 2022. He was the President of the IEEE Cellular Nanoscale Networks and Array (and Memristor Array) Computing Technical Committee from 2019 (2021) to 2021 (2023). He was honoured with the Darlington Best Paper Award from TCAS in 2023, and with Best Paper Awards from IJCTA in 2007, and from MOCAST in 2022 and 2020. He serves as Associate Editor for IEEE TCAS-I since 2023.

Fernando Corinto (Senior IEEE Member) Fernando Corinto received the Masters' Degree in Electronic Engineering and the Ph.D. degree in Electronics and Communications Engineering from the Politecnico di Torino, in 2001 and 2005 respectively. He also received the European Doctorate from the Politecnico di Torino, in 2005. Prof. Corinto was awarded a Marie Curie Fellowship in 2004.

He is currently Professor of Electrical Engineering with the Department of Electronics and Telecommunications, Politecnico di Torino. His research activities are mainly on nonlinear dynamical circuits and systems, complex/neural networks and memristor nanotechnology for optimization problems.

Prof. Corinto is co-author of 4 books, 10 book chapters and more than 170 international journal and conference papers. Since 2010, he is Senior Member of the IEEE. He is also Member of the IEEE CAS Technical Committees on “Cellular Nanoscale Networks and Array Computing” and “Nonlinear Circuits and Systems”. Prof. Corinto served as Vice-Chair of the IEEE North Italy CAS Chapter. Prof. Corinto has been Associated Editor of the IEEE Trans. on Circuits and Systems - I for 2014-2015. He is also in the Editorial Board and Review Editor of the International Journal of Circuit Theory and Applications sinceJanuary 2015. Prof. Corinto has been the Vice Chair of the COST Action “Memristors - Devices, Models, Circuits, Systems and Applications (MemoCiS)”. Prof. Corinto has been DRESDEN Senior Fellows at the Technische Universität Dresden in 2013 and 2017. Prof. Corinto is also August-Wilhelm Scheer visiting professor at Technische Universität München and member of the Institute for Advanced Study -Technische Universität München.

Stephan Menzel (Senior IEEE Member) received his PhD degree in Electronic Engineering (summa cum laude) from the RWTH Aachen University in 2012. Since 2012, he has been at the Peter Grünberg Institut (PGI-7) at Forschungszentrum Juelich GmbH as senior scienticst. He is now the head of the simulation group at the PGI-7, Forschungszentrum Juelich. His group developed simulation tools for resistive switching devices which are commonly available (www.emrl.de/Jart.html). From November 2021 – October 2022, he was a visiting scientist at IBM Research, Rüschlikon. He is associate editor of Scientific Reports (2015-). editor of MDPI Materials (2020-), associate editor of the IEEE Journal of the Electron Device Society, and associated editor of Frontiers in Neuroscience. He is member of the IEEE since 2012 (Senior Member since 2022) and member of the EDS, CAS and SSCS society and member of the CASS NC-TG, C. He is RCM member of ISCAS since 2022 and member of the technical committee of the IEEE IMW since 2023. His research interests include physics, characterization, modeling, and simulation of resistive switching (memristive) devices and computing-in-memory and neuromorphic computing circuits exploiting memristive devices.

Martin Ziegler received the Ph.D. degree in Physics from the University of Kiel, Germany, in 2009. He is currently a full professor and the Chair of Micro- and Nanoelectronic Systems at the Faculty of Electrical Engineering and Information Technology of the Technische Universität Ilmenau, Germany. He works in the field of neuromorphic engineering. His main research interests concern the transfer of biological learning and memory into electronic systems. For this purpose, he studies and applies memristive materials and devices, micro-electromechanical systems, and neuromorphic circuits. Currently, he is the spokesperson of the research groups MemWerk: Memristive Materials for Neuromorphic Electronics and NeuroSensEar: neuromorphic acoustic sensor technology for high-performance hearing aids funded by the Carl Zeiss Foundation and deputy spokesperson of the CRC 1461 – Neuroelectronics funded by the German Research Foundation. He is also coordinator of the ForLab Ilmenau for neuromorphic electronics, which is funded by the BMBF as part of the initiative Forschungslabore Mikroelektronik Deutschland.

Ronald Tetzlaff (Senior IEEE Member) is a Full Professor of Fundamentals of Electrical Engineering at the TUD | Dresden University of Technology, Germany. From 1999 to 2003 Ronald Tetzlaff was Associate Editor of the IEEE, Transactions on Circuits and Systems: part I. He was “Distinguished Lecturer” of the IEEE CAS Society (2001 to 2002). He is a member of the scientific committee of different international conferences. He was the chair of the 7th IEEE International Workshop on Cellular Neural Networks and their Applications (CNNA 2002) and organized several special sessions at circuit and systems related conferences. From 2005 to 2007 he was the chair of the IEEE Technical Committee Cellular Neural Networks & Array Computing. Ronald Tetzlaff is a member of the Informationstechnische Gesellschaft (ITG) and the German Society of Electrical Engineers and of the German URSI Committee. Ronald Tetzlaff is in the Editorial Board of the International Journal of Circuit Theory and Applications since 2007 and he is also in the Editorial Board of the IEEE, Transactions on Circuits and Systems: part II since 2016. He was Associate Editor of the AEÜ – International Journal of Electronics and Communications from 2008 to 2016. Ronald Tetzlaff was the chair of the 18th IEEE Workshop on Nonlinear Dynamics of Electronic Systems (NDES 2010), the chair of the 5th International Workshop on Seizure Prediction (IWSP5 2012) , the chair of the 21st European Conference on Circuit Theory and Design (ECCTD 2013), the chair of the 5th Memristor and Memristive Symposium 2016, and of the 15th IEEE International Workshop on Cellular Nanoscale Networks and their Applications (CNNA 2016). Since 2014 her serves as the leader of working group 2 (Memristor Theory, Modelling and Simulation) in the EU COST action MemoCIS (IC 1401) on Memristors – Devices, Models, Circuits, Systems and Applications. Ronald Tetzlaff serves as a reviewer for several journals and for the European Commission and was honoured with the Darlington Best Paper Award from IEEE TCAS in 2023.

Special Session on Smart Sensors and Sensor Networks

Smart sensors and sensor networks are advanced technologies that are increasingly present in various aspects of modern society and industry. Smart sensors are advanced devices with additional capabilities that collect, process, and transmit data about physical conditions or the environment, such as: temperature, humidity, pressure, brightness, sound, and more. These sensors are essentially complex mechatronic systems that use embedded processors and software to analyze the collected data, allowing them to make decisions or perform actions without direct human observation.

Sensor networks are groups of these intelligent sensors that are interconnected, most often wirelessly, to collect and share data within a specific space or system. The ability of sensor networks to automatically process and exchange information makes them extremely useful for a wide range of applications, including environmental monitoring, smart buildings, precision agriculture, healthcare, industrial automation, autonomous cars, and many other fields.

The proposed special session aims to showcase the most recent theoretical and experimental advancements in smart sensors and sensor networks. It will encompass a wide range of topics, from mathematical techniques for enhancing measurement accuracy to innovations in sensor materials and technologies. This scientific gathering will unite researchers from diverse academic disciplines to foster the exchange of knowledge, ideas, and collaboration within the multidisciplinary realm of sensor research. Moreover, the session will offer early-career scientists the chance to familiarize themselves with the latest developments, research trends, unresolved questions, and prospects in this dynamic field of study. The special session will encompass, among others, the following subjects:

·        Artificial intelligence techniques in sensors and sensor networks;

·        Micropower supplies;

·        Communications and communication protocols;

·        Innovative algorithms and data analysis software;

·        New materials and technologies for sensors;

·        Energy saving elements for sensors and sensor networks;

·        Autonomous and electric vehicles;

·        IoT for sustainable society;

·        Cybersecurity of sensor networks;

·        Mathematical methods to improve the accuracy of measurements.

Special Session Organizers:

Sandro Carrara is an IEEE Fellow for his outstanding record of accomplishments in the field of design of nanoscale biological CMOS sensors. He is also the recipient of the IEEE Sensors Council Technical Achievement Award in 2016 for his leadership in the emerging area of co-design in Bio/Nano/CMOS interfaces. He is a faculty member (MER) at the EPFL in Lausanne (Switzerland). He is former professor of optical and electrical biosensors at the Department of Electrical Engineering and Biophysics (DIBE) of the University of Genoa (Italy) and former professor of nanobiotechnology at the University of Bologna (Italy). Along his carrier, he published 7 books, one as author with Springer on Bio/CMOS interfaces and, more recently, a Handbook of Bioelectronics with Cambridge University Press. He also published more than 200 scientific papers and is author of 12 patents. He has been appointed as IEEE CASS Distinguished Lecturer for the years 2013-2014. His work received several international recognitions. He has been the General Chairman of the Conference IEEE BioCAS 2014, the premier worldwide international conference in the area of circuits and systems for biomedical applications.

Ali Meimandi received B.Sc degree in electrical engineering from Amirkabir University of Technology(Tehran Polytechnic), Tehran, Iran, and M.Sc. degree in electronic engineering from Politecnico di Milano, Milan, Italy, in 2018 and 2022, respectively. He is currently pursuing the Ph.D. degree in the BioCMOS Interfaces(BCI) Laboratory at École Polytechnique Fédérale de Lausanne, Lausanne, Switzerland. His research is focused on designing and implementing ultralow power and Ultralow area analog/mixed-signal IC for brain monitoring. His current research interests include biosensors, neural prosthesis, analog and digital CMOS design, ultra-low-power, and miniaturised CMOS integrated circuits to develop innovative biomedical systems.

Alireza Mafi received his B.Sc degree in electrical engineering from Iran University of Science and Technology, Tehran, Iran, and his M.Sc. degree in Microwave and Optical Communications from Sharif University of Technology, Tehran, Iran, in 2016 and 2021, respectively. He is currently pursuing a Ph.D. degree in the BioCMOS Interfaces(BCI) Laboratory at École Polytechnique Fédérale de Lausanne, Lausanne, Switzerland. His research is focused on edge computing for in-memory sensing using silicon nanowire memristive bio-sensors. His current research interests include biosensors, analog and digital CMOS design, and analog computing for in-memory sensing.

Nikolay Hinov graduated from the Technical University of Sofia with a Master's degree in Electronic Engineering and Microelectronics in 1995. In 1998 he holds a PhD with a dissertation on "Power electronics converters with industrial applications".He began her professional career at the Technical University of Sofia as a Assistant (1999) and Associate Professor in Industrial Electronics (2006) in the Department of Power Electronics.

Prof. Hinov's research interests are in the field of artificial intelligence; autonomous and electric vehicles; energy storage; mathematical modeling; control theory and applications; smart cities and smart grids; power electronic converters; power electronic systems. He has more than 280 scientific papers in professional journals and conferences, 10 patents and 3 utility models. Prof. Hinov serves as an associate editor, and reviewer for a number of professional journals and conferences. He is a Senior Member of the IEEE and the Board of the Union of Electronics, Electrical Engineering and Communications.

Valeri Mladenov graduated in Electrical Engineering (with distinction) from the Higher Institute for Mechanical and Electrical Engineering, Sofia (at present Technical University of Sofia), Bulgaria in 1985. He received his Ph.D. from the same institution in 1993. In 2019 he defenses a "Doctor of Sciences" thesis. Currently he is a Head of department Fundamentals of Electrical Engineering and Head of Neurocomputing Laboratory at the University.

Prof. Mladenov's research interests are in the field of neural networks, artificial intelligence, electronics and electrical engineering. He has received many international research fellowships. He has more than 300 scientific papers in professional journals and conferences. He is a co-author of ten books and manuals for students. As a member of several editorial boards, Prof. Mladenov serves as an editor in chief, associate editor, and reviewer for a number of professional journals and conferences. He is a Senior Member of the IEEE, Senior member of the International Neural Network Society (INNS) and a member of the International Council of Large Electric Systems, (SIGRE). He is an organizer and a chair of many International Conferences and Symposiums.